Update app.py

app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 import pandas as pd
+from matplotlib import pyplot as plt
 import twint 
 import nest_asyncio
 import multiprocessing.pool
@@ -13,6 +14,8 @@ import csv
 import urllib.request
 import IPython.display as ipd
 
+title = st.title('Loading')
+
 # Preprocess text (username and link placeholders)
 def preprocess(text):
     new_text = []
@@ -76,11 +79,11 @@ def get_tweets(username, limit=500, save_name=None):
     df.to_csv(save_name)
   return df
 
-st.title('Test')
+title = st.title('Twitter Sentiment Map Thingee')
 
 
 with st.form("my_form"):
-  st.write("Inside the form")
+  st.write("Parameters:")
   user = st.text_input("Twitter Username")
   n_tweets = st.slider('How Many Tweets', 20, 2000, 20)
 
@@ -94,5 +97,8 @@ if submitted:
   st.write("Calculating sentiments...")
   tweets['sentiment'] = tweets['tweet'].map(lambda s: combined_score(s))
   st.write("Average sentiment:", tweets.sentiment.mean())
-  st.pyplot.hexbin(tweets['tweet_length'], tweets['sentiment']*1, 
-           gridsize=20, bins=12, cmap='inferno')
+  fig, axs = plt.subplots(1, 2)
+  axs[0].hexbin(tweets['tweet_length'], tweets['sentiment']*1, 
+           gridsize=20, bins=12, cmap='inferno')
+  axs[1].scatter(tweets['tweet_length'], tweets['sentiment'])
+  st.pyplot(fig)