diff --git a/data/data_exploration.py b/data/data_exploration.py
index 6a36320168ffd6af154345769c48642ec369ddec..3974273b127ad534af6861735b5af5d876100a1e 100644
--- a/data/data_exploration.py
+++ b/data/data_exploration.py
@@ -5,13 +5,13 @@ import pandas as pd
 from constant import ALPHABET_UNMOD
 
 def length_distribution(data, plot=False, save=False, f_name='fig/data_exploration/length_distribution.png'):
-    max = 31
-    dist = np.zeros(max)
+    maximum = 31
+    dist = np.zeros(maximum)
     for seq in data:
         dist[len(list(seq)) - seq.count('-') * 2] += 1
 
     if plot or save:
-        plt.stairs(dist, range(max + 1), fill=True)
+        plt.stairs(dist, range(maximum + 1), fill=True)
         if plot:
             plt.show()
         if save:
@@ -64,9 +64,9 @@ def main():
     #data prosit
     df = pd.read_csv('data_prosit/data.csv')
     _ = length_distribution(df['sequence'],False ,True, '../fig/data_exploration/length_distribution_prosit.png')
-    _ = aa_distribution(df['sequence'], False, True, '../fig/data_exploration/aa_distribution_prosit.png')
+    _ = aa_distribution(df['mod_sequence'], False, True, '../fig/data_exploration/aa_distribution_prosit.png')
     retention_time_distribution(df['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_prosit.png')
-    df_unique = df[['sequence','irt_scaled']].groupby('sequence').mean()
+    df_unique = df[['mod_sequence','irt_scaled']].groupby('mod_sequence').mean()
     _ = length_distribution(df_unique.index, False, True, '../fig/data_exploration/length_distribution_prosit_unique.png')
     _ = aa_distribution(df_unique.index, False, True, '../fig/data_exploration/aa_distribution_prosit_unique.png')
     retention_time_distribution(df_unique['irt_scaled'], False, True,
@@ -75,32 +75,32 @@ def main():
     #prosit no cysteine
     df = pd.read_csv('data_prosit/data_noc.csv')
     _ = length_distribution(df['sequence'],False ,True, '../fig/data_exploration/length_distribution_prosit_noc.png')
-    _ = aa_distribution(df['sequence'], False, True, '../fig/data_exploration/aa_distribution_prosit_noc.png')
+    _ = aa_distribution(df['mod_sequence'], False, True, '../fig/data_exploration/aa_distribution_prosit_noc.png')
     retention_time_distribution(df['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_prosit_noc.png')
-    df_unique = df[['sequence','irt_scaled']].groupby('sequence').mean()
+    df_unique = df[['mod_sequence','irt_scaled']].groupby('mod_sequence').mean()
     _ = length_distribution(df_unique.index,False ,True, '../fig/data_exploration/length_distribution_prosit_noc_unique.png')
     _ = aa_distribution(df_unique.index, False, True, '../fig/data_exploration/aa_distribution_prosit_noc_unique.png')
     retention_time_distribution(df_unique['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_prosit_noc_unique.png')
 
     #isa
-    df = pd.read_csv('data_ISA/data_aligned_isa.csv')
-    _ = length_distribution(df['sequence'],False ,True, '../fig/data_exploration/length_distribution_isa.png')
-    _ = aa_distribution(df['sequence'], False, True, '../fig/data_exploration/aa_distribution_isa.png')
-    retention_time_distribution(df['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa.png')
-    df_unique = df[['sequence', 'irt_scaled']].groupby('sequence').mean()
-    _ = length_distribution(df_unique.index,False ,True, '../fig/data_exploration/length_distribution_isa_unique.png')
-    _ = aa_distribution(df_unique.index, False, True, '../fig/data_exploration/aa_distribution_isa_unique.png')
-    retention_time_distribution(df_unique['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa_unique.png')
-
-    #isa no cystéine
-    df = pd.read_csv('data_ISA/data_aligned_isa_noc.csv')
-    _ = length_distribution(df['sequence'],False ,True, '../fig/data_exploration/length_distribution_isa_noc.png')
-    _ = aa_distribution(df['sequence'], False, True, '../fig/data_exploration/aa_distribution_isa_noc.png')
-    retention_time_distribution(df['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa_noc.png')
-    df_unique = df[['sequence', 'irt_scaled']].groupby('sequence').mean()
-    _ = length_distribution(df_unique.index,False ,True, '../fig/data_exploration/length_distribution_isa_noc_unique.png')
-    _ = aa_distribution(df_unique.index, False, True, '../fig/data_exploration/aa_distribution_isa_noc_unique.png')
-    retention_time_distribution(df_unique['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa_noc_unique.png')
+    # df = pd.read_csv('data_ISA/data_aligned_isa.csv')
+    # _ = length_distribution(df['sequence'],False ,True, '../fig/data_exploration/length_distribution_isa.png')
+    # _ = aa_distribution(df['sequence'], False, True, '../fig/data_exploration/aa_distribution_isa.png')
+    # retention_time_distribution(df['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa.png')
+    # df_unique = df[['sequence', 'irt_scaled']].groupby('sequence').mean()
+    # _ = length_distribution(df_unique.index,False ,True, '../fig/data_exploration/length_distribution_isa_unique.png')
+    # _ = aa_distribution(df_unique.index, False, True, '../fig/data_exploration/aa_distribution_isa_unique.png')
+    # retention_time_distribution(df_unique['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa_unique.png')
+    #
+    # #isa no cystéine
+    # df = pd.read_csv('data_ISA/data_aligned_isa_noc.csv')
+    # _ = length_distribution(df['sequence'],False ,True, '../fig/data_exploration/length_distribution_isa_noc.png')
+    # _ = aa_distribution(df['sequence'], False, True, '../fig/data_exploration/aa_distribution_isa_noc.png')
+    # retention_time_distribution(df['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa_noc.png')
+    # df_unique = df[['sequence', 'irt_scaled']].groupby('sequence').mean()
+    # _ = length_distribution(df_unique.index,False ,True, '../fig/data_exploration/length_distribution_isa_noc_unique.png')
+    # _ = aa_distribution(df_unique.index, False, True, '../fig/data_exploration/aa_distribution_isa_noc_unique.png')
+    # retention_time_distribution(df_unique['irt_scaled'], False, True, '../fig/data_exploration/retention_time_distribution_isa_noc_unique.png')
 
 
 if __name__ == '__main__':