codes meets the requirement:

    For whitespace: LABEL, definition, definition source, alternative label
users can pass the label which needs to be processed and the file path as arguments into function clean_up_fn.
One example has been uploaded.

docs/VO-cleanup/clean_up_definition_field.py

@@ -0,0 +1,33 @@
+import pandas as pd
+import os
+from clean_up_data import clean_up_article
+
+def clean_up(cell):
+    if isinstance(cell, str):
+        cell = cell.strip()
+        cell = cell.capitalize()
+    return cell
+
+
+def clean_up_fn(columns_to_clean, file_paths):
+    for file_path in file_paths:
+        df = pd.read_csv(file_path)
+
+        # Apply the clean_up function to each specified column
+        for column in columns_to_clean:
+            if column in df.columns:
+                df[column] = df[column].apply(clean_up_article)
+
+        # Construct the output file path
+        dir_name, base_name = os.path.split(file_path)
+        name, ext = os.path.splitext(base_name)
+        output_file = os.path.join(dir_name, f"{name}_processed{ext}")
+
+        # Save the modified DataFrame to a new file
+        df.to_csv(output_file, index=False)
+        print(f"Modified data saved to {output_file}")
+
+
+# Example usage
+clean_up_fn(['definition', 'LABEL'], ["C:\\Users\\00000\\VO\\docs\\VO-cleanup\\term_editor\\processed_file2.csv",
+                                      'C:\\Users\\00000\\VO\\src\\templates\\vaccine_adjuvant.csv'])