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import pandas as pd
import ydata_profiling
import gradio as gr
from pydantic_settings import BaseSettings
import sweetviz as sv
def generate_report(file,type):
df = pd.read_csv(file) if file.name.endswith(".csv") else pd.read_excel(file)
if type == "pandas profiling":
return ydata_profiling.ProfileReport(df).to_html()
elif type == "sweetviz":
return sv.analyze(df).show_html(open_browser=True,
layout='widescreen',
scale=None)
# Custom HTML template for styling the report output
custom_html = """
<!DOCTYPE html>
<html>
<head>
<title>Data Profile Report</title>
<style>
body {
font-family: Arial, sans-serif;
margin: 0;
padding: 20px;
}
.container {
width: 80%;
margin: auto;
}
</style>
</head>
<body>
<div class="container">
{content}
</div>
</body>
</html>
"""
profile = gr.Interface(
generate_report,
[gr.File(file_types=['.csv','.xlsx'], label="Upload a CSV or Excel file"),
gr.Radio(["pandas profiling", "sweetviz"], label="Type of report", info="Explore the data")],
gr.HTML(label="Data profile Report", html_content=custom_html),
title="Excel sheet Profiling Report",
live=True,
)
cluster = gr.Interface(
generate_report,
[gr.File(file_types=['.csv','.xlsx'], label="Upload a CSV or Excel file"),
gr.Radio(["pandas profiling", "sweetviz"], label="Type of report", info="Explore the data")],
gr.HTML(label="Data profile Report", html_content=custom_html),
title="Excel sheet Profiling Report",
live=True,
)
demo = gr.TabbedInterface([cluster, profile], ["Product clustering", "Data Exploration"])
demo.launch(share=True) |