not sure what the best way to lay this out is

pa1.py

@@ -42,19 +42,19 @@ df_17 = create_df(get_full_dataset(id_17))
 df_18 = create_df(get_full_dataset(id_18))
 
 #summary statistics:
-print('5 Most Common Chicago Crimes in 2017: ',
-      df_17.primary_type.value_counts().head())
-print('5 Most Common Chicago Crimes in 2018: ',
-      df_18.primary_type.value_counts().head())
-print('5 Wards with Highest Volume of Crime in 2017: ', 
-      df_17.ward.value_counts().head())
-print('5 Wards with Highest Volume of Crime in 2018: ', 
-      df_18.ward.value_counts().head())
+print('10 Most Common Chicago Crimes in 2017:\n',
+      df_17.primary_type.value_counts().head(10))
+print('10 Most Common Chicago Crimes in 2018:\n',
+      df_18.primary_type.value_counts().head(10))
+print('10 Neighborhoods with Highest Volume of Crime in 2017:\n', 
+      df_17.community_area.value_counts().head(10))
+print('10 Neighborhoods with Highest Volume of Crime in 2018:\n', 
+      df_18.community_area.value_counts().head(10))
 
 arrest_rates_17 = df_17.arrest.value_counts()
 arrest_rates_18 = df_18.arrest.value_counts()
 
-print('Arrests Per Stop in 2017: ', (arrest_rates_17[1] / arrest_rates_17[0]))
-print('Arrests Per Stop in 2018: ', (arrest_rates_18[1] / arrest_rates_18[0]))
+print('Arrests Per Stop in 2017:\n', (arrest_rates_17[1] / arrest_rates_17[0]))
+print('Arrests Per Stop in 2018:\n', (arrest_rates_18[1] / arrest_rates_18[0]))