Update app.py

app.py

@@ -29,39 +29,41 @@ pytrends = TrendReq(hl='en-US', tz=360)
 
 st.title('Google Trends Analyzer')
 
-# Input for multiple keywords
-keywords = st.text_input('Enter keywords to analyze (comma-separated):', 'Streamlit, Data Science')
+# Sidebar for options
+with st.sidebar:
+    st.header('Analysis Options')
 
-# Geographical focus
-geo = st.text_input('Enter geographical region (e.g., US, FR, TH):', '')
+    # Input for multiple keywords as separate text boxes
+    keyword1 = st.text_input('Enter first keyword to analyze:', 'Streamlit')
+    keyword2 = st.text_input('Enter second keyword to analyze (optional):', '')
+    keyword3 = st.text_input('Enter third keyword to analyze (optional):', '')
 
-# Time range selection
-timeframe = st.selectbox('Select Time Range:', 
-                         ['today 12-m', 'today 3-m', 'today 1-m', 'today 5-y', 'all'])
+    # Geographical focus dropdown
+    countries = ['US', 'FR', 'TH', 'DE', 'IN', 'JP', 'BR', 'GB', 'CA', 'AU']
+    geo = st.selectbox('Select geographical region:', countries)
 
-# Category selection
-category = st.text_input('Enter category number (default is 0):', '0')
+    # Time range selection
+    timeframes = ['now 1-H', 'now 5-H', 'now 1-d', 'now 7-d', 'today 1-m', 'today 3-m']
+    timeframe = st.selectbox('Select Time Range:', timeframes)
 
-# Data Source selection
-data_source = st.selectbox('Select Data Source:', 
-                           ['Web Search', 'Image Search', 'News Search', 'Google Shopping', 'YouTube Search'])
+    # Data Source selection limited to specific options
+    data_source = st.selectbox('Select Data Source:', 
+                               ['Web Search', 'Image Search', 'YouTube Search'])
 
-if keywords:
+if keyword1 or keyword2 or keyword3:
     # Prepare the keywords list
-    kw_list = [kw.strip() for kw in keywords.split(',')]
-    
+    kw_list = [kw.strip() for kw in [keyword1, keyword2, keyword3] if kw]
+
     # Convert data source to pytrends parameter
     gprop_map = {
         'Web Search': '',
         'Image Search': 'images',
-        'News Search': 'news',
-        'Google Shopping': 'froogle',
         'YouTube Search': 'youtube'
     }
     gprop = gprop_map[data_source]
     
     # Fetch data from Google Trends
-    pytrends.build_payload(kw_list, cat=int(category), timeframe=timeframe, geo=geo, gprop=gprop)
+    pytrends.build_payload(kw_list, cat=0, timeframe=timeframe, geo=geo, gprop=gprop)
     interest_over_time_df = pytrends.interest_over_time()
 
     if not interest_over_time_df.empty: