Update app.py

app.py

@@ -3,6 +3,8 @@ import pandas as pd
 import numpy as np
 from sklearn.linear_model import LinearRegression
 import matplotlib.pyplot as plt
+import random
+import string
 
 # Remove the Streamlit default layout
 st.set_page_config(layout="wide")
@@ -14,8 +16,14 @@ data2 = pd.read_csv('tesla.csv')
 # Combine the datasets into a dictionary
 datasets = {'Google': data1, 'Tesla': data2}
 
+# Generate a random string for unique key generation
+def random_string(length):
+    letters = string.ascii_lowercase
+    return ''.join(random.choice(letters) for i in range(length))
+
 # Get the user's dataset selection
-selected_dataset = st.selectbox('Select Stock', list(datasets.keys()), key='dataset_selection')
+key = f'dataset_selection_{random_string(5)}'
+selected_dataset = st.selectbox('Select Stock', list(datasets.keys()), key=key)
 
 # Retrieve the selected dataset
 selected_data = datasets[selected_dataset]
@@ -58,7 +66,8 @@ axes[2].set_title(f'{selected_dataset} Daily Percentage Change in Stock Prices')
 # Add a submit button
 if st.button('Submit'):
     # Get the updated dataset selection
-    selected_dataset = st.selectbox('Select Stock', list(datasets.keys()), key='dataset_selection')
+    key = f'dataset_selection_{random_string(5)}'
+    selected_dataset = st.selectbox('Select Stock', list(datasets.keys()), key=key)
 
     # Retrieve the updated dataset
     selected_data = datasets[selected_dataset]