last_sunday / app.py
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Update app.py
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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()