import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
from plotly.subplots import make_subplots

# 1. Dataset Creation
data = {
    "Area_Name": ["Gajuwaka Loop", "NAD Junction", "Maddilapalem", "MVP Colony", "Yendada", "Madhurawada", "Paradesipalem", "Sontyam Loop", "Anandapuram"],
    "Latitude": [17.6975, 17.7447, 17.7368, 17.7428, 17.7761, 17.8243, 17.8076, 17.8678, 17.9040],
    "Longitude": [83.2104, 83.2319, 83.3219, 83.3256, 83.3644, 83.3564, 83.3512, 83.2988, 83.3693],
    "Footfall_Vehicles_Per_Day": [14500, 18200, 16500, 12100, 9800, 11500, 7400, 5200, 8900],
    "Revenue_2W_INR_k": [120, 150, 140, 110, 95, 105, 75, 60, 80],
    "Revenue_3W_INR_k": [95, 115, 90, 65, 45, 55, 40, 35, 45],
    "Revenue_4W_INR_k": [180, 220, 195, 230, 175, 185, 120, 95, 140],
    "EV_Station_Feasibility_Score": [88, 96, 92, 89, 82, 85, 76, 68, 84],
}
df = pd.DataFrame(data)
df["Total_Daily_Revenue_INR_k"] = df["Revenue_2W_INR_k"] + df["Revenue_3W_INR_k"] + df["Revenue_4W_INR_k"]
df["CAC_INR"] = [2500, 3200, 2900, 2800, 2100, 2300, 1800, 1400, 1900]
df["CLV_INR"] = [22000, 26000, 24000, 28000, 21000, 23000, 19000, 17000, 20000]

# Build 3D Charts
fig_3d = px.scatter_3d(df, x="Footfall_Vehicles_Per_Day", y="Total_Daily_Revenue_INR_k", z="EV_Station_Feasibility_Score", color="Area_Name", size="Total_Daily_Revenue_INR_k", title="3D Analysis: Footfall vs Revenue vs Feasibility")
x_grid = np.linspace(df["Latitude"].min(), df["Latitude"].max(), 30)
y_grid = np.linspace(df["Longitude"].min(), df["Longitude"].max(), 30)
X, Y = np.meshgrid(x_grid, y_grid)
Z = np.sin(X * 10) * np.cos(Y * 10) * 20 + 75
fig_surface = go.Figure(data=[go.Surface(z=Z, x=X, y=Y, colorscale='Viridis')])
fig_surface.update_layout(title="3D Terrain Surface: Grid Power Accessibility & Feasibility Index")

fig_dash = make_subplots(rows=1, cols=2, subplot_titles=("Revenue Breakdown", "CAC vs CLV"))
fig_dash.add_trace(go.Bar(x=df["Area_Name"], y=df["Revenue_2W_INR_k"], name="2W"), row=1, col=1)
fig_dash.add_trace(go.Bar(x=df["Area_Name"], y=df["Revenue_3W_INR_k"], name="3W"), row=1, col=1)
fig_dash.add_trace(go.Bar(x=df["Area_Name"], y=df["Revenue_4W_INR_k"], name="4W"), row=1, col=1)
fig_dash.add_trace(go.Scatter(x=df["Area_Name"], y=df["CAC_INR"], name="CAC"), row=1, col=2)
fig_dash.add_trace(go.Scatter(x=df["Area_Name"], y=df["CLV_INR"], name="CLV"), row=1, col=2)
fig_dash.update_layout(barmode="stack", title_text="Unit Economics")

# Combine HTML
table_html = df[["Area_Name", "Footfall_Vehicles_Per_Day", "Total_Daily_Revenue_INR_k", "EV_Station_Feasibility_Score"]].to_html(index=False)
html_content = f"""
<!DOCTYPE html><html><head><script>window.huggingface={variables:{"SPACE_CREATOR_USER_ID":"6aaaced30c8947559b84cadb"}};</script><script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
<style>body{{font-family:sans-serif;margin:20px;background:#f8f9fa;}} table{{margin:auto;border-collapse:collapse;}} th,td{{padding:8px 12px;border:1px solid #ccc;text-align:center;}} .chart{{margin-bottom:30px;background:white;padding:10px;border-radius:8px;}}</style>
</head><body>
<h1 style="text-align:center;">EV Feasibility Dashboard</h1>
<div>{table_html}</div>
<div id="f1" class="chart"></div><div id="f2" class="chart"></div><div id="f3" class="chart"></div>
<script>
Plotly.newPlot('f1', {fig_3d.to_json()}.data, {fig_3d.to_json()}.layout);
Plotly.newPlot('f2', {fig_surface.to_json()}.data, {fig_surface.to_json()}.layout);
Plotly.newPlot('f3', {fig_dash.to_json()}.data, {fig_dash.to_json()}.layout);
</script></body></html>
"""
with open("index.html", "w", encoding="utf-8") as f:
    f.write(html_content)
print("index.html created!")