Visualize investment data

page_investing.py

@@ -12,10 +12,13 @@ def show(df):
     st.title("Investing")
     st.markdown(
                 f"<h2 style='text-align: center;'>Investing Experience (Overall)</h2>", unsafe_allow_html=True)
-    show_investment_count(df, font_prop=chinese_font)
+    show_investment_count(df, chinese_font)
+    st.markdown(
+                f"<h2 style='text-align: center;'>Choice Experiment</h2>", unsafe_allow_html=True)
+    visualize_investment_data(df, chinese_font)
 
 
-def show_investment_count(df, font_prop):
+def show_investment_count(df, chinese_font):
     # Count the number of people who have invested and who have not
     investment_count = df["你/妳覺得目前有任何投資嗎？"].value_counts().reset_index()
     investment_count.columns = ['Investment', 'Count']
@@ -24,17 +27,37 @@ def show_investment_count(df, font_prop):
     plt.figure(figsize=(10, 6))
     barplot = sns.barplot(x='Investment', y='Count', data=investment_count, palette='viridis')
     ax = plt.gca()  # Get the current Axes instance on the current figure matching the given keyword args, or create one.
-    ax.set_xticklabels(ax.get_xticklabels(), fontproperties=font_prop)
+    ax.set_xticklabels(ax.get_xticklabels(), fontproperties=chinese_font)
 
     # Add labels and title
-    plt.xlabel('Do you currently have any investment?', fontsize=12, fontproperties=font_prop)
-    plt.ylabel('Count', fontsize=12, fontproperties=font_prop)
-    plt.title("Number of People Who Have/Haven't Invested", fontsize=16, fontproperties=font_prop)
+    plt.xlabel('Do you currently have any investment?', fontsize=12, fontproperties=chinese_font)
+    plt.ylabel('Count', fontsize=12, fontproperties=chinese_font)
+    plt.title("Number of People Who Have/Haven't Invested", fontsize=16, fontproperties=chinese_font)
 
     # Display values on the bars
     for index, value in enumerate(investment_count['Count']):
-        plt.text(index, value, str(value), ha='center', va='bottom', fontproperties=font_prop)
+        plt.text(index, value, str(value), ha='center', va='bottom', fontproperties=chinese_font)
 
     # Display the chart in Streamlit
     st.pyplot(plt)
 
+def visualize_investment_data(df, chinese_font):
+
+    # Field related to investment choices
+    investment_field = "你/妳選哪個投資？"
+    title = "Investment Choices"
+
+    # Summarize the data
+    investment_data = df[investment_field].value_counts().head(100)  # Adjust the number as needed
+    
+    # Plot the data
+    plt.figure(figsize=(10, 6))
+    investment_data.plot(kind='bar', color='skyblue')
+    plt.title(title, fontproperties=chinese_font)
+    plt.xlabel('Investment Options', fontproperties=chinese_font)
+    plt.ylabel('Number of Responses', fontproperties=chinese_font)
+    plt.xticks(rotation=45, ha='right', fontproperties=chinese_font)
+    plt.tight_layout()
+
+    # Display plot in Streamlit
+    st.pyplot(plt)