add twitter feature

app.py

@@ -77,12 +77,12 @@ def twitter_analyzer(keyword, max_tweets):
     df["Text"] = df["Text"].apply(ts.preprocess_text)
     df = sentiment_df(df)
 
-    df_ner = ner_df(df)
-    df_ner = df_ner[df_ner.Entity != keyword]
+    # df_ner = ner_df(df)
+    # df_ner = df_ner[df_ner.Entity != keyword]
 
     fig = plt.figure()
     df.groupby(["Label"])["Text"].count().plot.pie(autopct="%.1f%%", figsize=(6,6))
-    return fig, df[["URL", "Text", "Label", "Score"]], df_ner
+    return fig, df[["URL", "Text", "Label", "Score"]]
 
 if __name__ == "__main__":
 
@@ -122,17 +122,17 @@ if __name__ == "__main__":
                                                 overflow_row_behaviour='paginate',
                                                 wrap=True)
 
-                df_ner = gr.DataFrame(type="pandas",
-                                                label="Dataframe",
-                                                max_rows=(20,'fixed'),
-                                                overflow_row_behaviour='paginate',
-                                                wrap=True)
+                # df_ner = gr.DataFrame(type="pandas",
+                #                                 label="Dataframe",
+                #                                 max_rows=(20,'fixed'),
+                #                                 overflow_row_behaviour='paginate',
+                #                                 wrap=True)
 
 
         analyze_button.click(sentiment_ner, input_text, [sent_output, ner_output])
         submit_button.click(twitter_analyzer,
                     inputs=[keyword_textbox, max_tweets_component],
-                    outputs=[plot_component, dataframe_component, df_ner])
+                    outputs=[plot_component, dataframe_component])
 
         gr.Markdown(
                 """