app.py

import pandas as pd
import plotly.express as px
import gradio as gr

# Load data
df = pd.read_excel("report.xlsx", engine='openpyxl')
df['date'] = pd.to_datetime(df['date'], dayfirst=True, errors='coerce')
df['weekday'] = df['date'].dt.day_name()
df['hour'] = df['date'].dt.hour

# Define time blocks
bins = [-1, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 24]
labels = [
    'Before Starting', '11:00-11:59', '12:00-12:59', '13:00-13:59',
    '14:00-14:59', '15:00-15:59', '16:00-16:59', '17:00-17:59',
    '18:00-18:59', '19:00-19:59', 'After closing'
]
df['time_block'] = pd.cut(df['hour'], bins=bins, labels=labels, right=False)

# Weekday options in temporal order
ordered_days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
available_days = [d for d in ordered_days if d in df['weekday'].unique()]

# Function to generate plots
def plot_day(day):
    df_day = df[df['weekday'] == day]

    avg = (
        df_day.groupby('time_block')['total']
        .mean()
        .reindex(labels)
        .reset_index(name='Average')
    )
    count = (
        df_day.groupby('time_block')
        .size()
        .reindex(labels)
        .reset_index(name='Count')
    )
    total = (
        df_day.groupby('time_block')['total']
        .sum()
        .reindex(labels)
        .reset_index(name='Total')
    )

    fig1 = px.bar(avg, x='time_block', y='Average', title=f"Average total per sale ({day})")
    fig2 = px.bar(count, x='time_block', y='Count', title=f"Number of sales ({day})")
    fig3 = px.bar(total, x='time_block', y='Total', title=f"Total revenue ({day})")

    return fig1, fig2, fig3

# Gradio app with custom layout
with gr.Blocks() as demo:
    gr.Markdown("# 🛍️ Retail Demand Dashboard")
    gr.Markdown("Visualize sales metrics by time block, filtered by weekday")

    with gr.Row():
        dropdown = gr.Dropdown(choices=available_days, label="Select Day")

    with gr.Row():
        avg_plot = gr.Plot(label="Average Total")
    with gr.Row():
        count_plot = gr.Plot(label="Number of Sales")
    with gr.Row():
        revenue_plot = gr.Plot(label="Total Revenue")

    dropdown.change(
        fn=plot_day,
        inputs=dropdown,
        outputs=[avg_plot, count_plot, revenue_plot]
    )

# Launch app
if __name__ == "__main__":
    demo.launch()