working app

app.py

@@ -1,37 +1,26 @@
 import streamlit as st
-from streamlit_option_menu import option_menu
 from PIL import Image
 
-from apps import home, dashboard, models,demo
 
-#st.set_page_config(layout="wide")
+st.set_page_config(layout="wide")
 image = Image.open('data/logo.png')
 image=image.resize((100,100))
-header = st.container()
+APP_SUB_TITLE = "by Omdena Milan chapter 👇 (https://omdena.com/local-chapters/milan-italy-chapter/)"
+with st.sidebar:
+    logo = st.image(image)
+    st.caption(APP_SUB_TITLE)
 
-apps = [
-    {"func": home.app, "title": "Home", "icon": "house"},
-    {"func": dashboard.app, "title": "Dashboard", "icon": "bar-chart"},
-    {"func": models.app, "title": "Models", "icon": "cpu"},
-    {"func": demo.app, "title": "Demo", "icon": "cloud-upload"},
-]
+import streamlit as st
 
-titles = [app["title"] for app in apps]
-titles_lower = [title.lower() for title in titles]
-icons = [app["icon"] for app in apps]
 
-#Using "with" notation
+st.title("AI for sustainable agriculture and foood systems:Use of Satellite Imagery")
 
-with st.sidebar:
-    logo = st.image(image)
-    selected = option_menu(
-        "Main Menu",
-        options=titles,
-        icons=icons,
-        menu_icon="cast",
-    )
+st.markdown('''Over five weeks in October 2022, Omdena-Milan Local Chapter collaborators completed
+a local chapter challenge on applying Artificial Intelligence (AI) and Satellite imagery for
+sustainable agri-food systems.To this end, the Omdena-Milan Local Chapter collaborators explored
+various machine learning (ML) and data science techniques and geographic information systems (GIS)
+methods. The team worked on different tasks which are independent of each other to address the same 
+project goal. For demonstration, the team integrated all of them into one dashboard with good usability
+for non-technical decision-makers. 
+''')
 
-for app in apps:
-    if app["title"] == selected:
-        app["func"]()
-        break

apps/demo.py

@@ -1,6 +0,0 @@
-import streamlit as st
-
-
-
-def app():
-    st.title("Demo")

apps/home.py

@@ -1,14 +0,0 @@
-import streamlit as st
-
-
-def app():
-
-    st.title("AI for sustainable agriculture and foood systems:Use of Satellite Imagery")
-    st.markdown('''Over five weeks in October 2022, Omdena-Milan Local Chapter collaborators completed
-    a local chapter challenge on applying Artificial Intelligence (AI) and Satellite imagery for
-    sustainable agri-food systems.To this end, the Omdena-Milan Local Chapter collaborators explored
-    various machine learning (ML) and data science techniques and geographic information systems (GIS)
-    methods. The team worked on different tasks which are independent of each other to address the same 
-    project goal. For demonstration, the team integrated all of them into one dashboard with good usability
-    for non-technical decision-makers. 
-    ''')

apps/models.py

@@ -1,6 +0,0 @@
-import streamlit as st
-
-
-
-def app():
-    st.title("Models")

{apps → pages}/dashboard.py

@@ -6,55 +6,13 @@ import folium
 from PIL import Image
 from streamlit_folium import st_folium
 
-def app():
-    
-
-    APP_TITLE = "Italy Agrifoods Data"
-    image = Image.open('data/logo.png')
-    image=image.resize((100,100))
-    st.title(APP_TITLE)
-    #st.set_page_config(layout="wide")
-
-    st.title(APP_TITLE)
-
-
-    image = Image.open('data/logo.png')
-    image=image.resize((100,100))
-
-
-    #load data
-    df_olives = pd.read_csv("data/Italy_regions_with_code_grapes_olives.csv")    
-    df_cereals = pd.read_csv("data/Italy_regions_with_code_cereals.csv")
-    df_veg = pd.read_csv("data/Italy_regions_with_code_fresh_veg.csv")
-    df_fruit = pd.read_csv("data/Italy_regions_with_code_fruit.csv")
-    df = df_fruit
-    year = ''
-    region = "Abruzzo"
+APP_TITLE = "Italy Agrifoods Data"
+APP_SUB_TITLE = "by Omdena Milan chapter 👇 (https://omdena.com/local-chapters/milan-italy-chapter/)"
+image = Image.open('data/logo.png')
+image=image.resize((100,100))
 
 
 
-    #st.write(df.shape)
-    #st.write(df.head())
-
-
-    product = display_product()
-    col1, col2 = st.columns(2)
-
-    #display map
-    with col1:
-        year = display_time_filters(df)
-
-    #st.header('{Header!!!!}')
-    region = display_map(df, year)
-
-    with col2:
-        #display metric
-        region = display_state_filter(df, region)
-        metric_title = f"{product} Harvested Production in Quintals {region} - Italy: {year}"
-        display_yield(df, year, region, metric_title)
-        
-
-
 def display_time_filters(df):
     year_list = list(df['TIME'].unique())
     year_list.sort()
@@ -108,3 +66,55 @@ def display_map(df, year):
             return 'Puglia'
     return region_name
 
+def main():
+    st.set_page_config(APP_TITLE, layout="wide")
+    st.title(APP_TITLE)
+    
+
+    image = Image.open('data/logo.png')
+    image=image.resize((100,100))
+
+    with st.sidebar:
+        logo = st.image(image)
+        st.caption(APP_SUB_TITLE)
+
+    #load data
+    df_olives = pd.read_csv("data/Italy_regions_with_code_grapes_olives.csv")    
+    df_cereals = pd.read_csv("data/Italy_regions_with_code_cereals.csv")
+    df_veg = pd.read_csv("data/Italy_regions_with_code_fresh_veg.csv")
+    df_fruit = pd.read_csv("data/Italy_regions_with_code_fruit.csv")
+    df = df_fruit
+    year = ''
+    region = ""
+    
+    
+
+    #st.write(df.shape)
+    #st.write(df.head())
+
+    
+    product = display_product()
+    col1, col2 = st.columns([2,1])
+    
+    #display map
+    with col2:
+        #display metric
+        year = display_time_filters(df)
+        region = display_state_filter(df, region)
+        metric_title = f"{product} Harvested Production in Quintals {region} - Italy: {year}"     
+        display_yield(df, year, region, metric_title)
+    
+    with col1:
+         region = display_map(df, year)      
+        
+        
+    #st.header('{Header!!!!}')
+   
+    
+
+    
+    #metric_title = f"Harvested Production in Quintals {region} - Italy: {year}" 
+
+if __name__ == "__main__":
+    main()
+    

pages/demo.py

@@ -0,0 +1,15 @@
+import streamlit as st
+import pandas as pd
+import geopandas as gpd
+from millify import millify
+import folium
+from PIL import Image
+from streamlit_folium import st_folium
+
+APP_TITLE = "Italy Agrifoods Data"
+APP_SUB_TITLE = "by Omdena Milan chapter 👇 (https://omdena.com/local-chapters/milan-italy-chapter/)"
+image = Image.open('data/logo.png')
+image=image.resize((100,100))
+#st.set_page_config(layout="wide")
+
+st.title(APP_TITLE)