Update app.py

Added final code

app.py

@@ -1,20 +1,4 @@
-# Library imports
-import streamlit as st
-import twarc
-import twarc_csv
-import pandas as pd
-import numpy as np
-from requests_oauthlib import OAuth1Session
-import json
-from datetime import datetime, timezone, timedelta
-from twarc.client2 import Twarc2
-from twarc_csv import DataFrameConverter #CSVConverter
-from textblob import TextBlob
-
-# Create header to display information about the data
-#st.header("This app runs a sentiment analysis on the replies to a tweet. To begin, \
-#          copy the URL from the tweet you want to analyze, and paste it below.")
-
+# HEADER
 st.header("This app runs a sentiment analysis on the replies to a Tweet from Facebook when they announced their rebranding to Meta on October 28th, 2021")
             
 st.subheader("The Tweet analyzed for this project can be viewed here: ")
@@ -22,5 +6,39 @@ st.subheader("The Tweet analyzed for this project can be viewed here: ")
 st.markdown("![Alt Text](https://twitter.com/Meta/status/1453795115701440524)")
 
 
-# Display the sentiment score
-st.write("Tweet sentiment score: I'm currently working on this, stay tuned! (JMansfield 12/27/21)")
+# LIBRARY IMPORTS
+import streamlit as st
+import pandas as pd
+import sys
+from streamlit import cli as stcli
+
+
+# DATA IMPORT
+# Import data from "df_redacted.csv" as a dataframe
+df_redacted = pd.read_csv('df_redacted.csv')
+
+
+# DISPLAY RESULTS
+# Create dictionary of sentiment categories and corresponding scores
+values = df_redacted['sentiment_score'].value_counts(dropna=False).keys().tolist()
+counts = df_redacted['sentiment_score'].value_counts(dropna=False).tolist()
+value_dict = dict(zip(values, counts))
+
+# Calculate the max of all 3 sentiment categories
+sentiment = max(value_dict, key=value_dict.get)
+
+
+def main():
+    # Display the count for each sentiment category and overall sentiment of the tweet replies
+    st.write('Highest sentiment category for the replies to the Facebook Tweet announcing Meta: ', sentiment)
+    st.write(value_dict)
+    # Display histogram of count for each sentiment category
+    st.bar_chart(df_redacted['sentiment_score'].value_counts())
+
+
+if __name__ == '__main__':
+    if st._is_running_with_streamlit:
+        main()
+    else:
+        sys.argv = ["streamlit", "run", sys.argv[0]]
+        sys.exit(stcli.main())