added initial code #1

preprocess_uk.py

@@ -0,0 +1,43 @@
+import pandas as pd
+import os
+
+# Preprocess data
+vote_counter = -1
+data = pd.DataFrame()
+
+name_column = 'Member'
+vote_column = 'Vote'
+
+column_to_filename = {}
+
+voting_features = {'Aye':0, 'No':1, 'No Vote Recorded':2}
+for dirname, _, filenames in os.walk('./uk/csv'):
+    for filename in filenames:
+        vote_counter += 1
+        print(os.path.join(dirname, filename))
+        
+        # Read title rows
+        title_df = pd.read_csv(os.path.join(dirname, filename),nrows=(3),skip_blank_lines=True,header=None)
+    
+        # Read data rows
+        df = pd.read_csv(os.path.join(dirname, filename),skiprows=(10))
+        
+        # Give each voting behaviour type an identifier from 0 to len(voting_features) - 1
+        df[vote_column].replace(voting_features, inplace=True)
+        
+        #Replace the vote column name
+        vote_column_name = f'vote_{vote_counter}'
+        df=df.rename(columns={vote_column:vote_column_name})
+         
+        # Map column name of vote to title -> allows retrieving what the vote was about
+        column_to_filename[vote_column_name] = title_df.iat[2,0]
+                
+        if data.empty:
+            # if first file that is loaded set data equal to data from first file
+            data = df[[name_column, vote_column_name]]
+        else:
+            # merge data with already loaded data 
+            data = data.merge(df[[name_column, vote_column_name]], on=name_column)
+
+print(column_to_filename)
+print(data)