app.py

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import requests

st.set_page_config(page_title="SWOT Analysis Radar Chart", page_icon="💪")

st.sidebar.subheader("About the Author")

image_url = "https://github.com/benjaminjvdm/streamlit-author/blob/main/Untitled%20design(1)(1).png?raw=true"
try:
    response = requests.get(image_url)
    print(f"Image URL: {image_url}")
    response.raise_for_status()
    image = response.content
    st.sidebar.image(image, caption="Moon Benjee (문벤지)")
except requests.exceptions.RequestException as e:
    st.sidebar.error(f"Error loading image: {e}")

st.sidebar.markdown(
    """
    This app was Built with ❤️ by **Benjee(문벤지)**.
    You can connect with me on: [LinkedIn](https://www.linkedin.com/in/benjaminjvdm/)
    """
)

st.title("SWOT Analysis Radar Chart")
st.header("Enter SWOT Factors and Importance")

with st.form("swot_form"):
    st.write("Importance levels: Normal (1), High (2), Highest (3)")

    # Function to get factors and importance values
    def get_factors_and_importance(category_name):
        factors_input = st.text_input(f"{category_name} (comma-separated):")
        factors_list = [f.strip() for f in factors_input.split(",") if f.strip()]
        importance_values = []
        for i, factor in enumerate(factors_list):
            importance = st.number_input(f"Importance of '{factor}':", min_value=1, max_value=3, value=2, key=f"{category_name}_{i}") #Unique key
            importance_values.append(importance)
        return factors_list, importance_values

    # Get input for each category
    strengths_list, strengths_importance = get_factors_and_importance("Strengths")
    weaknesses_list, weaknesses_importance = get_factors_and_importance("Weaknesses")
    opportunities_list, opportunities_importance = get_factors_and_importance("Opportunities")
    threats_list, threats_importance = get_factors_and_importance("Threats")

    submitted = st.form_submit_button("Generate Radar Chart")


if submitted:
    # Data preparation
    categories = ['Strengths', 'Weaknesses', 'Opportunities', 'Threats']
    category_values = {
        'Strengths': strengths_importance,
        'Weaknesses': weaknesses_importance,
        'Opportunities': opportunities_importance,
        'Threats': threats_importance
    }

    # Calculate average importance for each category
    avg_values = [np.mean(v) if v else 0 for v in category_values.values()]

    # Optimized Plot Settings
    label_offset = 0.2
    label_size = 10  # Explicitly define label_size here

    # Plot radar chart
    angles = np.linspace(0, 2 * np.pi, len(categories), endpoint=False).tolist()
    avg_values += avg_values[:1]
    angles += angles[:1]

    fig = plt.figure(figsize=(10, 10))
    ax = fig.add_subplot(111, polar=True)
    ax.set_rgrids([])  
    ax.set_xticks([])

    ax.plot(angles, avg_values, 'o-', linewidth=2, color='blue')
    ax.fill(angles, avg_values, alpha=0.25, color='lightblue')

    ax.grid(alpha=0.2)  
    plt.ylim(0, 3.5)

    plt.title("SWOT Analysis", size=16)

    # Display category labels and average values on the points themselves
    for i, category in enumerate(categories):
        angle = angles[i]
        avg_importance = avg_values[i]
        ax.text(angle, avg_importance + 0.2, f"{category} ({avg_importance:.1f})", 
                ha='center', va='center', size=label_size, fontweight='bold')

    # Display the chart
    st.pyplot(fig)