Added some changes

app.py

@@ -15,7 +15,7 @@ from tensorflow.keras.models import load_model
 
 st.set_page_config(
         page_title="FANG Stock Prediction",
-        page_icon=":etherium:",
+        page_icon=":currency:",
         layout="wide"
     )
 
@@ -68,7 +68,8 @@ def test_data_predict(lstm_model):
 stock_lstm = load_model("fang_stock_prediction.h5")
 
 predict_prices = test_data_predict(lstm_model=stock_lstm)
-valid = test_data_GOOG.filter(['Adj Close'])
+valid = pd.DataFrame()
+valid['Actual Data'] = test_data_GOOG.filter(['Adj Close'])
 valid['Predictions'] = predict_prices
 
 stock_data = ['Stock Price of Google From 2007 - 2021', 'Actual Stock Price and Model Prediction']
@@ -76,8 +77,11 @@ stock_data = ['Stock Price of Google From 2007 - 2021', 'Actual Stock Price and
 selection = st.selectbox("Select country", stock_data)
 if selection == 'Stock Price of Google From 2007 - 2021':
   st.line_chart(data_GOOG.filter(['Adj Close']))
+  st.dataframe(data_GOOG.filter(['High', 'Low', 'Open', 'Close', 'Adj Close']), use_container_width=True)
 elif selection == 'Actual Stock Price and Model Prediction':
-  testing = st.line_chart(data_GOOG.filter(['Adj Close'])).add_rows(valid)
+  st.line_chart(data_GOOG.filter(['Adj Close'])).add_rows(valid)
+  st.dataframe(valid, use_container_width=True)
+  st.text(valid.shape)
 
 # fig, ax = plt.subplots()
 # plt.figure(figsize=(10, 8))

requirements.txt

@@ -1,6 +1,6 @@
 numpy>=1.17.3
 pandas==1.3.5
-streamlit==1.10.0
+streamlit==1.14.0
 tensorflow==2.6.0
 pandas-datareader==0.10.0
 sklearn==0.0