page_investing.py

import streamlit as st
import pandas as pd
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
import seaborn as sns

@st.cache_data
def show(df):
    # Load the Chinese font
    chinese_font = FontProperties(fname='mingliu.ttf', size=12)
    st.title("Investing")
    show_investment_count(df, font_prop=chinese_font)


def show_investment_count(df, font_prop):
    # 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']

    # Create a bar chart using seaborn
    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)

    # 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)

    # 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)

    # Display the chart in Streamlit
    st.pyplot(plt)