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