Add some changes

app.py

@@ -24,7 +24,7 @@ st.write("# Welcome to FANG Stock Prediction Dashboard :bitcoin:")
 company_ticker = ['FB', 'AAPL', 'TSLA', 'GOOG', 'NVDA']
 
 start_date = dt.datetime(2007, 1, 1)
-end_date = dt.datetime(2020, 12, 13)
+end_date = dt.datetime(2021, 12, 31)
 data_FB = pdr.DataReader(company_ticker[0], 'yahoo', start_date, end_date)
 # data_AAPL = pdr.DataReader(company_ticker[1], 'yahoo', start_date, end_date)
 # data_TSLA = pdr.DataReader(company_ticker[2], 'yahoo', start_date, end_date)
@@ -36,7 +36,7 @@ scaled_data_FB = scaler.fit_transform(data_FB.filter(['Adj Close']).values.resha
 scaled_data_GOOG = scaler.fit_transform(data_GOOG.filter(['Adj Close']).values.reshape(-1, 1))
 prediction_days = 89
 
-test_start = dt.datetime(2020, 12, 31)
+test_start = dt.datetime(2021, 12, 31)
 test_end = dt.datetime.now()
 test_data_FB = pdr.DataReader(company_ticker[0], 'yahoo', test_start, test_end)
 # test_data_AAPL = pdr.DataReader(company_ticker[1], 'yahoo', test_start, test_end)
@@ -77,11 +77,10 @@ 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)
+  st.dataframe(data_GOOG, use_container_width=True)
 elif selection == 'Actual Stock Price and Model Prediction':
   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))
@@ -101,4 +100,4 @@ real_data = np.reshape(real_data, (real_data.shape[0], real_data.shape[1], 1))
 
 real_prediction = stock_lstm.predict(real_data)
 real_prediction = scaler.inverse_transform(real_prediction)
-st.text(f"Real prediction stock prices on Google is {real_prediction[0]}")
+st.text(f"Real-time prediction stock prices on Google is {real_prediction[0]}")

requirements.txt

@@ -1,6 +1,6 @@
 numpy>=1.17.3
 pandas==1.3.5
-streamlit==1.14.0
+streamlit>=3.10.0
 tensorflow==2.6.0
 pandas-datareader==0.10.0
 sklearn==0.0