import gradio as gr import pandas as pd from datetime import datetime import matplotlib.pyplot as plt from pywaffle import Waffle import math import numpy as np # Load the life expectancy data from the World Bank # This is a direct link to the CSV data for life expectancy at birth, total (years) file = "life_expectancy_2023_world_back_data.csv" # Read the CSV data, skipping the first 4 rows of metadata try: df = pd.read_csv(file) life_expectancy_data = df[['Country','Life Expectancy at Birth']].copy() # life_expectancy_data.columns = ['Country', 'Life Expectancy'] life_expectancy_data.dropna(inplace=True) countries = sorted(life_expectancy_data['Country'].unique()) except Exception as e: print(f"Error loading data: {e}") countries = ["Error loading country data"] life_expectancy_data = pd.DataFrame(columns=['Country', 'Life Expectancy']) def create_life_calendar(name, birth_year, country): """ Creates a graphical calendar of life, with each year represented as a row of 52 dots (weeks). """ # --- Input Validation and Data Fetching --- if not all([name, birth_year, country]) or country.startswith("Error"): return None, "Please provide your name, birth year, and select a country." if life_expectancy_data.empty: return None, "Life expectancy data is unavailable. Cannot generate calendar." try: birth_year = int(birth_year) country_data = life_expectancy_data[life_expectancy_data['Country'] == country] if country_data.empty: return None, f"Sorry, life expectancy data for {country} is not available." life_expectancy = int(country_data['Life Expectancy at Birth'].iloc[0]) except (ValueError, TypeError): return None, "Please enter a valid birth year." # --- Calculations --- now = datetime.now() current_year = now.year current_week = now.isocalendar()[1] age = current_year - birth_year # --- Plotting Setup --- fig, ax = plt.subplots(figsize=(10, life_expectancy / 10), dpi=120) # Define colors past_color = '#d9534f' # Red future_color = '#5cb85c' # Green dot_size = 10 weeks_in_year = 52 # --- Vectorized Plotting --- # Create arrays for all x and y coordinates all_weeks = np.tile(np.arange(1, weeks_in_year + 1), life_expectancy) # y-coordinates: these need to be in the order of plotting (top to bottom) # so, for year 1, y is life_expectancy - 1; for year life_expectancy, y is 0 all_years_plot_coord = np.repeat(np.arange(life_expectancy - 1, -1, -1), weeks_in_year) # Determine colors for all dots colors = [] for year_display in range(1, life_expectancy + 1): # Iterate through years from 1 to life_expectancy if year_display < age: colors.extend([past_color] * weeks_in_year) elif year_display == age: # Weeks up to current_week are past, the rest are future colors.extend([past_color] * (current_week)) # current_week is 1-indexed colors.extend([future_color] * (weeks_in_year - current_week)) else: colors.extend([future_color] * weeks_in_year) # Plot all dots at once ax.scatter(all_weeks, all_years_plot_coord, c=colors, s=dot_size, marker='o') # --- Formatting and Labels --- # Add year/age labels to the y-axis ax.set_yticks(range(0, life_expectancy, 5)) # Labels should correspond to the 'Age' represented by the y-coordinate # If y = life_expectancy - year, then year = life_expectancy - y # So the age label for y-coordinate 'i' is 'life_expectancy - i' ax.set_yticklabels([str(life_expectancy - i) for i in range(0, life_expectancy, 5)]) ax.set_ylabel("Age", fontsize=12) # Configure x-axis for weeks ax.set_xticks([1, 13, 26, 39, 52]) ax.set_xticklabels(["Week 1", "Week 13", "Week 26", "Week 39", "Week 52"]) ax.set_xlabel("Week of the Year", fontsize=12) ax.xaxis.tick_top() ax.xaxis.set_label_position('top') # Remove the plot frame/spines for a cleaner look for spine in ['left', 'right', 'bottom']: ax.spines[spine].set_visible(False) # Set plot limits ax.set_xlim(0, weeks_in_year + 1) ax.set_ylim(-1, life_expectancy) # Ensure y-axis covers all years, with a small buffer # Create a custom legend legend_elements = [ plt.Line2D([0], [0], marker='o', color='w', label='Past Week', markerfacecolor=past_color, markersize=10), plt.Line2D([0], [0], marker='o', color='w', label='Future Week', markerfacecolor=future_color, markersize=10) ] ax.legend(handles=legend_elements, loc='center left', bbox_to_anchor=(1.02, 0.5), fontsize=12) fig.tight_layout() weeks_left = (life_expectancy - age) * 52 - current_week message = f"Hello {name}, based on a life expectancy of {life_expectancy} in {country}, you have approximately {weeks_left:,} weeks remaining." return fig, message # Create the Gradio interface with gr.Blocks(css=".center-text {text-align: center;}",theme=gr.themes.Soft()) as demo: gr.Markdown( """ # Last Sunday Get reminded of how many Sundays remain :) This app shows you a visualization of how many Sunday are remaining in your life. It's created to remind oneself that time in life is limited and is not to be wasted. It's very easy to use. You simply enter your name and date of birth. Taking life expectancy as 80 years, it tells you how many weeks are left until you die. Inspired by the PARAS CHOPRA [Last Sunday](https://chromewebstore.google.com/detail/the-last-sunday-reminder/aiojhapcgfgmiacbbjfgedhlcchmpelh?hl=en) app. """ ,elem_classes="center-text" ) with gr.Row(): name_input = gr.Textbox(label="Your Name") birth_year_input = gr.Number(label="Your Birth Year", minimum=1900, maximum=datetime.now().year) country_input = gr.Dropdown(choices=countries, label="Your Country") # output_text = gr.Textbox(label="Your Remaining Sundays") # with gr.Row(): # expired_input = gr.Number(label="Expired Sundays (Red Dots)", value=1560) # remaining_input = gr.Number(label="Remaining Sundays (Green Dots)", value=2600) generate_button = gr.Button("Generate My Life Calendar", variant="primary") with gr.Column(): output_plot = gr.Plot() output_text = gr.Label() generate_button.click( fn=create_life_calendar, inputs=[name_input, birth_year_input, country_input], outputs=[output_plot, output_text] ) demo.launch()