Add environment page

app.py

@@ -4,6 +4,7 @@ import page_attitudes
 import page_demographics
 import page_shopping
 import page_investing
+import page_environment
 import page_ai
 import page_personas
 import page_tests
@@ -43,6 +44,8 @@ if st.sidebar.button("Shopping"):
     st.session_state['page'] = 'Shopping'
 if st.sidebar.button("Investing"):
     st.session_state['page'] = 'Investing'
+if st.sidebar.button("Environment"):
+    st.session_state['page'] = 'Environment'
 if st.sidebar.button("AI Companion"):
     st.session_state['page'] = 'AI'
 if st.sidebar.button("Tests"):
@@ -66,6 +69,8 @@ elif st.session_state['page'] == 'Shopping':
     page_shopping.show(df)
 elif st.session_state['page'] == 'Investing':
     page_investing.show(df)
+elif st.session_state['page'] == 'Environment':
+    page_environment.show(df)
 elif st.session_state['page'] == 'AI':
     page_ai.show(df)
 elif st.session_state['page'] == 'Tests':

page_environment.py

@@ -0,0 +1,38 @@
+import streamlit as st
+import pandas as pd
+from matplotlib.font_manager import FontProperties
+import matplotlib.pyplot as plt
+import seaborn as sns
+from fields.likert_fields import likert_fields
+
+@st.cache_data
+def show(df):
+    # Load the Chinese font
+    chinese_font = FontProperties(fname='notosans.ttf', size=12)
+    st.title("Environment")
+
+    st.markdown(
+                f"<h2 style='text-align: center;'>Ranking Experiment</h2>", unsafe_allow_html=True)
+    visualize_ecosystem_sensitivity(df, chinese_font)
+
+
+
+def visualize_ecosystem_sensitivity(df, chinese_font):
+  
+    # Field related to ecosystem sensitivity to environmental degradation
+    ecosystem_field = "你/妳覺得如何依照生態系對環境惡化的敏感度來排名？"
+
+    # Summarize the data
+    ecosystem_data = df[ecosystem_field].value_counts().head(20)  # Adjust the number as needed
+    
+    # Plot the data
+    plt.figure(figsize=(10, 6))
+    ecosystem_data.plot(kind='bar', color='forestgreen')
+    plt.title('Ecosystem Sensitivity to Environmental Degradation', fontproperties=chinese_font)
+    plt.xlabel('Sensitivity Ranking', fontproperties=chinese_font)
+    plt.ylabel('Number of Responses', fontproperties=chinese_font)
+    plt.xticks(rotation=45, ha='right', fontproperties=chinese_font)
+    plt.tight_layout()
+
+    # Display the plot in Streamlit
+    st.pyplot(plt)