Better solution for splitting and combining columns.

Convert-EUProcessingFactorsDB/Convert-EUProcessingFactorsDB.py

@@ -143,8 +143,7 @@ efsa_combined = dataset.efsa.sheet.merge(
     right_on=['FromFX', 'FXToRpc'], how='left').assign(
     )
 
-# First let's copy the columns which we want in the output unaltered
-#                So this is a copy  FROM FIELD : TO FIELD
+# First let's copy the columns which we want in the output unaltered so far
 efsa_combined.mcra.copycolumn({'ParamName Active Substance': 'SubstanceName',
                                'Matrix Code': 'idFoodUnProcessed',
                                'Raw Primary Commodity': 'FoodUnprocessedName',
@@ -195,8 +194,7 @@ else:
 
 
 ###############################################
-# Request by Waldo, please also add the description of the Processing Type.
-# So, again, a left join :-)
+# Also add the description of the Processing Type.
 efsa_combined = efsa_combined.merge(
     # Left join with processing type sheet,
     dataset.processing_type.sheet,
@@ -222,15 +220,9 @@ if dataset.food_composition.sheet is not None:
     fcs = dataset.food_composition.sheet[(
         dataset.food_composition.sheet['idToFood'].str.startswith('P') &
         dataset.food_composition.sheet['idFromFood'].str.contains('-'))]
-    # Now split the first column
-    fs = pd.DataFrame()
-    # Bit of a mess, to combine again.
-    fs[['idFromFood-Left', 'idFromFood-Right']] = \
-        fcs['idFromFood'].str.rsplit('-', n=1, expand=True)
-    fcs = fcs.merge(fs, left_index=True, right_index=True)
-    # New columns is properly joined now
-    fcs['idToFood-PC'] = fcs.loc[:, ('idToFood', 'idFromFood-Right')].apply(
-        lambda x: '-'.join(x.dropna()), axis=1)
+    fcs[(fcs['idToFood'].str.startswith('P') & fcs['idFromFood'].str.contains('-'))].assign()
+
+    fcs=fcs.mcra.splitjoin(name='idToFood-PC', split='idFromFood', join='idToFood')
     # Finally a left join to combine
     efsa_combined = efsa_combined.merge(
         # Left join with processing type sheet,

Convert-EUProcessingFactorsDB/mcra.py

@@ -50,6 +50,30 @@ class McraAccessor:
         for col in columnnames:
             self._obj[col] = ''
 
+    def splitjoin(self, name, split, join,
+                  split_sep='-', right_split=True, join_sep='-'):
+        '''
+        Splits a column, and then joins the result with another column
+        '''
+        # Due to the SettingWithCopyWarning we do it a bit cumbersome
+        df = pd.DataFrame()
+        df[join] = self._obj[join]
+        if right_split:
+            df[split] = self._obj[split].str.rsplit(split_sep, n=1).str[1]
+        else:
+            df[split] = self._obj[split].str.rsplit(split_sep, n=1).str[0]
+
+        df[name]= df.loc[:, (join, split)].apply(
+                    lambda x: '-'.join(x.dropna()), axis=1)
+        df=df.drop([join,split],axis=1)
+
+        #self._obj[name] = df.loc[:, (name)]
+        ##self._obj[name] = df[name]
+        self._obj=self._obj.merge(df, left_index=True, right_index=True)
+        #self._obj.loc[name] = df[name]
+        print(self._obj)
+        return self._obj
+
 
 class DataFile:
     '''