errors correction

src/utils/data_parsing.py

@@ -90,7 +90,7 @@ class JcampParser:
     @property
     def meta_data_st_(self):
         me = self.metadata_.drop("concentrations", axis = 1)
-        me = me.drop(me.columns[(me == '').all()], axis = 1).applymap(lambda x: x.upper() if isinstance(x, str) else x)  
+        me = me.drop(me.columns[(me == '').all()], axis = 1).map(lambda x: x.upper() if isinstance(x, str) else x)
         meta_data_st = me.loc[:,me.nunique(axis=0) > 1]
         return meta_data_st
 
@@ -124,7 +124,7 @@ class CsvParser:
 
     @property
     def meta_data_st_(self):
-        me = self.non_float.applymap(lambda x: x.upper() if isinstance(x, str) else x)  
+        me = self.non_float.map(lambda x: x.upper() if isinstance(x, str) else x)
         meta_data_st = me.loc[:,me.nunique(axis=0) > 1]
         return meta_data_st
 

src/utils/miscellaneous.py

@@ -24,7 +24,7 @@ def download_results(data, export_name):
 def data_split(x, y):
     from kennard_stone import train_test_split
     # Split data into training and test sets using the kennard_stone method and correlation metric, 25% of data is used for testing
-    X_train, X_test, y_train, y_test  = train_test_split(x, y, test_size = 0.25, random_state = 42)
+    X_train, X_test, y_train, y_test  = train_test_split(x, y, test_size = 0.25)
     train_index, test_index = np.array(X_train.index), np.array(X_test.index)
     return X_train, X_test, y_train, y_test, train_index, test_index