diff --git a/python/report.py b/python/report.py
index 427f89e..b2710ab 100644
--- a/python/report.py
+++ b/python/report.py
@@ -19,13 +19,18 @@
 # localize
 
 sentences = { 'it':
-                [f'Ciao, ecco le ultime {args.nexp} spese:',
-                 f'Totale speso dal',
-                 f'Totale per ogni utente dal'],
+                [f'Ciao, ecco le ultime {args.nexp} spese dal',
+                 f'Bilancio',
+                 f'Bilancio per ogni utente',
+                 f'Uscite',
+                 f'Uscite per ogni utente',
+                 f'Entrate',
+                 f'Entrate per ogni utente'
+                 ],
               'en':
-                [f'Hi, here\'s the latest {args.nexp} expenses:',
-                 f'Total sum of expenses since',
-                 f'Sum of expenses for every user since']}
+                [f'Hi, here\'s the latest {args.nexp} expenses since',
+                 f'Total balance since',
+                 f'Balance for every user since']}
 
 
 # load CSV
@@ -34,29 +39,54 @@
 df['FloatValue'] = df[['Value']].astype(float)
 
 recent = df.sort_values(by='dt', ascending=False)
+startdate = recent.dt.iloc[-1].date()
 
 # latest N expenses
-print(sentences[args.lang][0] + '\n')
+print('{0} {1}:\n'.format(
+    sentences[args.lang][0],
+    startdate))
 
 print(
     recent[['ID', 'Time', 'Value', 'User', 'Notes']]
     .head(int(args.nexp))   # only print latest args.nexp expenses
     .to_string(index=False))
 
-# totals of whole
-startdate = recent.dt.iloc[-1].date()
+# balance
 ntot = recent.FloatValue.sum()
 
-print('\n{0} {1}:\n{2:.2f} euro'.format(
+print('\n{0}:\n{1:.2f} euro'.format(
     sentences[args.lang][1],
-    startdate,
     abs(ntot)))
 
 usertot = pd.DataFrame(recent[['User','FloatValue']].groupby('User', group_keys=True).sum())
 
-print('\n{0} {1}:'.format(
-    sentences[args.lang][2],
-    startdate))
+print('\n{0}:'.format(sentences[args.lang][2]))
 
 for user,value in usertot.iterrows():
     print('{0}: {1:.2f} euro'.format(user,abs(value.values[0])))
+
+# outgoing
+outgoing = recent.loc[recent['FloatValue'] < 0].FloatValue.sum()
+userOut = pd.DataFrame(recent[['User','FloatValue']].loc[recent['FloatValue'] < 0].groupby('User', group_keys=True).sum())
+
+print('\n{0}:\n{1:.2f} euro'.format(
+    sentences[args.lang][3],
+    abs(outgoing)))
+
+print('\n{0}:'.format(sentences[args.lang][4]))
+
+for user,value in userOut.iterrows():
+    print('{0}: {1:.2f} euro'.format(user,abs(value.values[0])))
+
+# incoming
+incoming = recent.loc[recent['FloatValue'] >= 0].FloatValue.sum()
+userIn = pd.DataFrame(recent[['User','FloatValue']].loc[recent['FloatValue'] >= 0].groupby('User', group_keys=True).sum())
+
+print('\n{0}:\n{1:.2f} euro'.format(
+    sentences[args.lang][5],
+    abs(incoming)))
+
+print('\n{0}:'.format(sentences[args.lang][6]))
+
+for user,value in userIn.iterrows():
+    print('{0}: {1:.2f} euro'.format(user,abs(value.values[0])))