fixed global df

app.py

@@ -70,6 +70,7 @@ def scrape(keyword_list):
 
 def get_example(dataset):
     df = pd.read_csv(dataset + '.csv')
+    return df
 
 def give_emoji_free_text(text):
     """
@@ -129,7 +130,7 @@ def tokenize(text):
 
     return tokens
 
-def cleaning():
+def cleaning(df):
     df.rename(columns = {'tweet':'original_tweets'}, inplace = True)
 
     # Apply the function above and get tweets free of emoji's
@@ -504,11 +505,11 @@ def optimized_bertopic():
 def main(dataset, model):
     keyword_list = dataset.split(',')
     if dataset in examples:
-        get_example(keyword_list)
+        df = get_example(keyword_list)
         place_data = 'test'
     else:
         place_data = str(scrape(keyword_list))
-    cleaning()
+    cleaning(df)
 
     print(df)
     if model == 'LDA':