app.py

import marimo

__generated_with = "0.11.4"
app = marimo.App(width="medium")


@app.cell
def _(mo):
    mo.md("""# Exploration on Smartphone Consumer Trends in India""")
    return


@app.cell(hide_code=True)
def _():
    import marimo as mo
    import polars as pl

    dataset_raw = pl.read_csv("dataset/diabetes_binary_health_indicators_BRFSS2015.csv")
    dataset_raw.head()
    return dataset_raw, mo, pl


@app.cell
def _(dataset_raw):
    dataset_priors = dataset_raw.select(["Diabetes_binary", "HighBP", "HighChol", "Stroke", "HeartDiseaseorAttack"])
    dataset_priors.head()
    return (dataset_priors,)


@app.cell
def _():
    from sklearn.naive_bayes import BernoulliNB
    from sklearn.metrics import accuracy_score, confusion_matrix, classification_report
    from sklearn.model_selection import train_test_split
    return (
        BernoulliNB,
        accuracy_score,
        classification_report,
        confusion_matrix,
        train_test_split,
    )


if __name__ == "__main__":
    app.run()